Nadiia Davydiuk, Elisha Krieg, Jens Gaitzsch, Patrick M. McCall, Günter K. Auernhammer, Mu Yang, Joseph B. Tracy, Sara Bals, Wolfgang J. Parak, Nicholas A. Kotov, Luis M. Liz-Marzán, Andreas Fery, Matthew Faria, Quinn A. Besford
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The rising danger of AI-generated images in nanomaterials science and what we can do about it
Generative AI has made it trivial to generate fake microscopy images that are indistinguishable from real images, even for experts. As researchers in nanoscience, it is time for us to face this reality and discuss strategies to conserve the integrity of our discipline.
期刊介绍:
Nature Nanotechnology is a prestigious journal that publishes high-quality papers in various areas of nanoscience and nanotechnology. The journal focuses on the design, characterization, and production of structures, devices, and systems that manipulate and control materials at atomic, molecular, and macromolecular scales. It encompasses both bottom-up and top-down approaches, as well as their combinations.
Furthermore, Nature Nanotechnology fosters the exchange of ideas among researchers from diverse disciplines such as chemistry, physics, material science, biomedical research, engineering, and more. It promotes collaboration at the forefront of this multidisciplinary field. The journal covers a wide range of topics, from fundamental research in physics, chemistry, and biology, including computational work and simulations, to the development of innovative devices and technologies for various industrial sectors such as information technology, medicine, manufacturing, high-performance materials, energy, and environmental technologies. It includes coverage of organic, inorganic, and hybrid materials.